The system would be used to detect flaws on long duration orbiting space platforms. Such platforms require inspection for collisions with micro-meteorites and space debris; material degradation due to prolonged exposure to the harsh space environment; and geometrical mismatches at mechanical interfaces prior to assembly operations. Telerobotic operation of the automated inspection system would save considerable astronaut time and minimize EVA associated risks.
In the absence of lighting variations, viewpoint differences, and sensor noise, the detection of change could be obtained by a process of simple differencing - subtracting an earlier reference image from a new inspection image. However, lighting variation due to orbital motion can cause surface appearance to change drastically. Lack of viewpoint repeatability caused by mechanical flexibility in the robot arm leads to mis-registration of reference and inspection images. Sensor noise is inevitable, and the resulting detection problems must be well characterized and managed.
In the automated inspection system, ambient light variability is compensated by utilizing compensated reference and inspection image data. Compensation requires two image data sets, the first is illuminated only with the ambient light and the second is illuminated with the ambient light as well as an artificial illuminator. The first data set is subtracted from the second to give a compensated image that appears as if it were taken with the artificial illuminator alone. In order to have an adequate signal-to-noise ratio, the artificial illuminator must provide illumination comparable to (or more than) the ambient light. This is difficult for a low-powered continuous illuminator. Instead, an electronic strobe unit is utilized to concentrate all of the artificial illumination into a very short time interval. When the electronic shutter in the camera is set to operate only over this short time interval, the strobe provided illumination is comparable to that provided from the ambient light. The strobe illumination also enables imaging from a moving platform since it does not have the time lags associated with a continuous illuminators.
Without registration error compensation, subtracting reference and inspection images results in a number of ``false edges'' in the differenced image. A Gauss-Newton iterative method is used by the automated inspection system to perform reference-to-inspection image registration prior to making the comparison. The residual sum-of-squares between the actual and an estimated picture is used as an evaluation function to indicate the degree of match between the inspection data and a transformed reference image. Mis-registration is corrected by finding a suitable transformation of the reference image so that the residual is close to zero.
In addition, quantitative tools have been developed to allow an explicit tradeoff between detection probability and the false-error probability. Depending on the flaw model and noise parameters, detection thresholds can be chosen to achieve a given level of performance.
Flaw recognition is made computationally tractable by analyzing the images only in the region where differences have been found, and that too at the most appropriate scale of resolution. This ``scale-space'' technique maximizes flaw information while at the same time minimizing the amount of distracting information. In this solution, the optimum scale for analyzing a sensor-produced image is selected from prior knowledge of image texture/features. Following this, edge detection is performed at an optimum scale. Finally, pattern recognition is used at different scales, followed by flaw classification. Examples of images from a laboratory mockup of space platform modules have been used to test the concept.
For more information see:
J. Balaram and S. Hayati, ``Telerobotic Inspection For Remote Space Platforms'', ESA/INRIA Workshop on Computer Vision for Space Applications, Antibes, France, September 1993.
J. Balaram and K.V. Prasad, ``Automated Inspection For Remote Telerobotic Operations'', IEEE Conference on Robotics & Automation, Atlanta, Ga. May 1993.
Point of Contact:
J. Balaram,
Mail Stop 198-219
Jet Propulsion Laboratory
4800 Oak Grove Drive
Pasadena, CA 91109
818-354-6770
J.Balaran@jpl.nasa.gov
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